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%matplotlib inline


    

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from __future__ import division

from matplotlib import pyplot as plt
import numpy as np


    

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coeffs = [3.3, -4.2, 0.1, 7]
x = np.sort(5 * np.random.rand(100) - 2)
y = np.poly1d(coeffs)(x)
y += 10 * np.random.rand(100) - 5

coeff_fit = np.polyfit(x, y, 3)


    

In [19]:

    

plt.figure(figsize=(10, 5))
plt.scatter(x, y)
plt.plot(x, np.poly1d(coeff_fit)(x), color='orange', lw=3)
plt.grid()


    

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from IPython.html.widgets import interact


    

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COEFFS = 10 * np.random.rand(7) - 5

@interact(noise=(0, 30), degree=(1, len(COEFFS)))
def fit_example(noise, degree):
    coeffs = COEFFS[:degree]
    x = np.sort(5 * np.random.rand(100) - 2)
    y = np.poly1d(coeffs)(x)
    y += 2*noise * np.random.rand(100) - noise
    
    coeff_fit = np.polyfit(x, y, len(coeffs)-1)
    plt.figure(figsize=(10, 5))
    plt.scatter(x, y)
    plt.plot(x, np.poly1d(coeff_fit)(x), color='orange', lw=3)
    
    print coeffs
    print coeff_fit


    

    




[-3.84666746  4.57352943 -1.69941742  0.70895099 -0.03706637  3.32703348]
[-4.45780574  6.29660738 -0.16170832 -4.73939774  0.2010279   7.82574162]






    

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